Speech-based depression detection has attracted significant attention over the last years. A debated problem is whether it is better to use language (what people say), paralanguage (how they say it) or a combination of the two. This article addresses the question through the analysis of a Gated Multimodal Unit trained to weight modalities according to how effectively they account for the condition of a speaker (depressed or nondepressed). The experiments involved 29 individuals diagnosed with depression and 30 non-depressed participants. Besides an accuracy of 83.0% (F1 score 80.0%), the results show that the Gated Multimodal Unit tends to give more weight to paralanguage. However, the relative contribution of language tends to be higher, to a statistically significant extent, in the case of nondepressed speakers.

Language or paralanguage, This is the problem: Comparing depressed and non-depressed speakers through the analysis of gated multimodal units

Esposito A.;
2021

Abstract

Speech-based depression detection has attracted significant attention over the last years. A debated problem is whether it is better to use language (what people say), paralanguage (how they say it) or a combination of the two. This article addresses the question through the analysis of a Gated Multimodal Unit trained to weight modalities according to how effectively they account for the condition of a speaker (depressed or nondepressed). The experiments involved 29 individuals diagnosed with depression and 30 non-depressed participants. Besides an accuracy of 83.0% (F1 score 80.0%), the results show that the Gated Multimodal Unit tends to give more weight to paralanguage. However, the relative contribution of language tends to be higher, to a statistically significant extent, in the case of nondepressed speakers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/460783
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